K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores

Journal of Clinical Bioinformatics
Arnold I EmersonJoel A Malek

Abstract

Network biology currently focuses primarily on metabolic pathways, gene regulatory, and protein-protein interaction networks. While these approaches have yielded critical information, alternative methods to network analysis will offer new perspectives on biological information. A little explored area is the interactions between domains that can be captured using domain co-occurrence networks (DCN). A DCN can be used to study the function and interaction of proteins by representing protein domains and their co-existence in genes and by mapping cancer mutations to the individual protein domains to identify signals. The domain co-occurrence network was constructed for the human proteome based on PFAM domains in proteins. Highly connected domains in the central cores were identified using the k-core decomposition technique. Here we show that these domains were found to be more evolutionarily conserved than the peripheral domains. The somatic mutations for ovarian, breast and prostate cancer diseases were obtained from the TCGA database. We mapped the somatic mutations to the individual protein domains and the local false discovery rate was used to identify significantly mutated domains in each cancer type. Significantly mutated dom...Continue Reading

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Citations

Dec 2, 2015·Journal of Chemical Information and Modeling·Isidro Cortes-Ciriano, Andreas Bender

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Software Mentioned

R
DAVID
PANDIT
Ensembl
Perl Perl API
PFAM
PfamScan
locfdr
Cytoscape

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